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We propose a method to obtain phase portraits for stochastic systems. Starting from the Fokker-Planck equation, we separate the dynamics into a convective and a diffusive part. We show that stable and unstable fixed points of the convective…

Statistical Mechanics · Physics 2018-05-03 Marc Mendler , Johannes Falk , Barbara Drossel

Microscopic instability and macroscopic flow pattern resulting from colliding plasmas are studied analytically in support of laboratory experiments. The plasma flows are assumed to stream radially from two separate centers. In a…

Plasma Physics · Physics 2018-11-13 Mikhail Malkov , Vladimir Sotnikov

Techniques from numerical bifurcation theory are very useful to study transitions between steady fluid flow patterns and the instabilities involved. Here, we provide computational methodology to use parameter continuation in determining…

Numerical Analysis · Mathematics 2020-11-12 S. Baars , J. P. Viebahn , T. E. Mulder , C. Kuehn , F. W. Wubs , H. A. Dijkstra

This is a comprehensive report on the phase transition between two turbulent states of electroconvection in nematic liquid crystals, which was recently found by the authors to be in the directed percolation (DP) universality class [K. A.…

Statistical Mechanics · Physics 2009-11-19 Kazumasa A. Takeuchi , Masafumi Kuroda , Hugues Chaté , Masaki Sano

Topological defects resulted from boundary constraints in confined liquid crystals have attracted extensive research interests. In this paper, we use numerical simulation to study the phase transition dynamics in the context of stochastic…

Soft Condensed Matter · Physics 2018-10-03 Yucheng Hu , Liu Hong , Weihua Deng

Flow Matching (FM) (also referred to as stochastic interpolants or rectified flows) stands out as a class of generative models that aims to bridge in finite time the target distribution $\nu^\star$ with an auxiliary distribution $\mu$,…

Machine Learning · Statistics 2024-09-16 Marta Gentiloni Silveri , Giovanni Conforti , Alain Durmus

In fully-developed pressure-driven flow, the spreading of a dissolved solute is enhanced in the flow direction due to transverse velocity variations in a phenomenon now commonly referred to as Taylor-Aris dispersion. It is well understood…

Fluid Dynamics · Physics 2022-10-04 Garam Lee , Alan Luner , Jeremy Marzuola , Daniel M. Harris

In this paper, we numerically study the stochastic and the deterministic occasional uncoupling methods of effecting identical synchronized states in low dimensional, dissipative, diffusively coupled, chaotic flows that are otherwise not…

Adaptation and Self-Organizing Systems · Physics 2020-07-07 Anupam Ghosh , Sagar Chakraborty

In recent years, Rectified flow (RF) has gained considerable popularity largely due to its generation efficiency and state-of-the-art performance. In this paper, we investigate the degree to which RF automatically adapts to the intrinsic…

Machine Learning · Statistics 2026-02-24 Saptarshi Roy , Alessandro Rinaldo , Purnamrita Sarkar

Turbulent systems exhibit a remarkable multi-scale complexity, in which spatial structures induce scale-dependent statistics with strong departures from Gaussianity. In Fourier space, this is reflected by pronounced phase synchronization. A…

We introduce a minimization formulation for the determination of a finite-dimensional, time-dependent, orthonormal basis that captures directions of the phase space associated with transient instabilities. While these instabilities have…

Computational Physics · Physics 2016-04-27 Hessam Babaee , Themistoklis Sapsis

We study a diffusion approximation for a model of stochastic motion of a particle in one spatial dimension. The velocity of the particle is constant but the direction of the motion undergoes random changes with a Poisson clock. Moreover,…

Functional Analysis · Mathematics 2022-04-21 Adam Bobrowski , Tomasz Komorowski

Predictability of flow is examined in a barotropic vorticity model that admits low frequency regime transitions between zonal and dipolar states. Such transitions in the model were first studied by Bouchet and Simonnet (2009) and are…

Chaotic Dynamics · Physics 2016-05-20 B. T. Nadiga , T. J. O'Kane

Although redistribution of red blood cells at bifurcated vessels is highly dependent on flow rate, it is still challenging to quantitatively express the dependency of flow rate in plasma skimming due to nonlinear cellular interactions. We…

Quantitative Methods · Quantitative Biology 2017-05-03 Jiho Yang , Sung Sic Yoo , Tae-Rin Lee

The use of spectral proper orthogonal decomposition (SPOD) to construct low-order models for broadband turbulent flows is explored. The choice of SPOD modes as basis vectors is motivated by their optimality and space-time coherence…

Fluid Dynamics · Physics 2021-09-22 Tianyi Chu , Oliver T. Schmidt

This paper exposes a novel exploratory formalism, which end goal is the numerical simulation of the dynamics of a cloud of particles weakly or strongly coupled with a turbulent fluid. Giventhe large panel of expertise of the list of…

Analysis of PDEs · Mathematics 2019-10-21 Ludovic Goudenège , Adam Larat , Julie Llobell , Marc Massot , David Mercier , Olivier Thomine , Aymeric Vié

We study a mesoscopic model for the flow of amorphous solids. The model is based on the key features identified at the microscopic level, namely peri- ods of elastic deformation interspersed with localised rearrangements of parti- cles that…

Materials Science · Physics 2017-02-08 Alexandre Nicolas , Jean-Louis Barrat

In this letter, it is shown numerically that in plane Poiseuille flow and before the threshold of equilibrium turbulence defined by the directed-percolation universality class, a sparse turbulent state in form of localized turbulent band…

Fluid Dynamics · Physics 2018-02-07 Jianjun Tao , Bruno Eckhardt , Xiangming Xiong

This study deals with continuous limits of interacting one-dimensional diffusive systems, arising from stochastic distortions of discrete curves with various kinds of coding representations. These systems are essentially of a…

Statistical Mechanics · Physics 2011-09-09 Guy Fayolle , Cyril Furtlehner

We develop a framework for non-asymptotic analysis of deterministic samplers used for diffusion generative modeling. Several recent works have analyzed stochastic samplers using tools like Girsanov's theorem and a chain rule variant of the…

Machine Learning · Computer Science 2023-03-07 Sitan Chen , Giannis Daras , Alexandros G. Dimakis
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